In recent years, researchers of deep neural networks (DNNs)-based facial expression recognition (FER) have reported results showing that these approaches overcome the limitations of conventional machine learning-based FER approaches. However, as DNN-...
Computer vision and deep learning are clearly demonstrating a capability to create engaging cognitive applications and services. However, these applications have been mostly confined to powerful Graphic Processing Units (GPUs) or the cloud due to the...
Recognizing facial expression has attracted much more attention due to its broad range of applications in human–computer interaction systems. Although facial representation is crucial to final recognition accuracy, traditional handcrafted repre...
The real-time detection of facial skin problems is crucial for improving dermatological health, yet its practical implementation remains challenging. Early detection and timely intervention can significantly enhance skin health while reducing the fin...
Drowsiness on the road is a widespread problem with fatal consequences; thus, a multitude of systems and techniques have been proposed. Among existing methods, Ghoddoosian et al. utilized temporal blinking patterns to detect early signs of drowsiness...
The rapid growth of high-dimensional biometric data requires fast and accurate similarity search methods for real-time applications. This study proposes, for the first time, two efficient parallel implementations of the exact Sorting-based Nearest Ne...
A proper colouring of a plane graph G is called facially homogeneous if it uses the same number of colours for every face of G. We study various sufficient conditions of facial homogeneous colourability of plane graphs, its relation to other facial c...
Despite advanced machine learning methods, the implementation of emotion recognition systems based on real-world video content remains challenging. Videos may contain data such as images, audio, and text. However, the application of multimodal models...
Microexpressions are subtle facial movements that occur within an extremely brief time frame, often revealing suppressed emotions. These expressions hold significant importance across various fields, including security monitoring and human–comp...
Face recognition systems typically face actual challenges like facial pose, illumination, occlusion, and ageing that significantly impact the recognition accuracy. In this paper, a robust face recognition system that uses Multi-task Cascaded Convolut...
In this paper, we propose a new model for conditional video generation (GammaGAN). Generally, it is challenging to generate a plausible video from a single image with a class label as a condition. Traditional methods based on conditional generative a...
Facial expression recognition is an interesting and challenging subject. Considering the nonlinear manifold structure of facial images, a new kernel-based manifold learning method, called kernel discriminant isometric mapping (KDIsomap), is proposed....
Deep learning became an important image classification and object detection technique more than a decade ago. It has since achieved human-like performance for many computer vision tasks. Some of them involve the analysis of human face for application...
Given that most cues exchanged during a social interaction are nonverbal (e.g., facial expressions, hand gestures, body language), individuals who are blind are at a social disadvantage compared to their sighted peers. Very little work has explored s...
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Facial fracture patients are seen in a Level 1 trauma hospital. In our institution, we manage many patients with facial fractures and carry out more than 150 surgical procedures every year. Open reduction and internal fixation is our management of ch...
Developing a user interface (UI) suitable for headset environments is one of the challenges in the field of augmented reality (AR) technologies. This study proposes a hands-free UI for an AR headset that exploits facial gestures of the wearer to reco...
Emotion Recognition is attracting the attention of the research community due to the multiple areas where it can be applied, such as in healthcare or in road safety systems. In this paper, we propose a multimodal emotion recognition system that relie...
Recently, real-time facial expression recognition has attracted more and more research. In this study, an automatic facial expression real-time system was built and tested. Firstly, the system and model were designed and tested on a MATLAB environmen...
Computer recognition of human activity is an important area of research in computer vision. Human activity recognition (HAR) involves identifying human activities in real-life contexts and plays an important role in interpersonal interaction. Artific...
Occlusion or posture change of the face in natural scenes has typical asymmetry; however, an asymmetric face plays a key part in the lack of information available for facial expression recognition. To solve the problem of low accuracy of asymmetric f...
Spatial Transformer Networks are considered a powerful algorithm to learn the main areas of an image, but still, they could be more efficient by receiving images with embedded expert knowledge. This paper aims to improve the performance of convention...
With the rapid development of virtual reality (VR) technology and the market growth of social network services (SNS), VR-based SNS have been actively developed, in which 3D avatars interact with each other on behalf of the users. To provide the users...
Facial expression recognition (FER) in the wild is a challenging task due to some uncontrolled factors such as occlusion, illumination, and pose variation. The current methods perform well in controlled conditions. However, there are still two issues...
Affective computing is an increasingly important outgrowth of Artificial Intelligence, which is intended to deal with rich and subjective human communication. In view of the complexity of affective expression, discriminative feature extraction and co...
Facial expression recognition (FER) techniques can be widely used in human-computer interaction, intelligent robots, intelligent monitoring, and other domains. Currently, FER methods based on deep learning have become the mainstream schemes. However,...
This study aims to investigate and propose a machine learning approach that can accurately detect alcohol consumption by analyzing the thermal patterns of facial features. Thermal images from the Tufts Face Database and self-collected images were uti...
In facial landmark detection, extracting shape-indexed features is widely applied in existing methods to impose shape constraint over landmarks. Commonly, these methods crop shape-indexed patches surrounding landmarks of a given initial shape. All la...
This paper proposes an innovative technique for representing multidimensional datasets using icons inspired by Chernoff faces. Our approach combines classical projection techniques with the explicit assignment of selected data dimensions to avatar (f...
Face detection technology is essential for surveillance and security projects; however, algorithms designed to detect faces in color images often struggle in poor lighting conditions. In this paper, we describe the development of an embedded vision s...
Facial expression recognition (FER) utilizes artificial intelligence for the detection and analysis of human faces, with significant applications across various scenarios. Our objective is to deploy the facial emotion recognition network on mobile de...
Face verification and identification traditionally follow a symmetric matching approach, where the same model (e.g., ResNet-50 vs. ResNet-50) generates embeddings for both gallery and query images, ensuring compatibility. However, real-world scenario...
Mountainous roads are severely affected by environmental factors such as insufficient lighting and shadows from tree branches, which complicates the detection of drivers’ facial features and the determination of fatigue states. An improved meth...
Facial recognition is a method of identifying or authenticating the identity of people through their faces. Nowadays, facial recognition systems that use multispectral images achieve better results than those that use only visible spectral band image...
Recently, intelligent personal assistants, chat-bots and AI speakers are being utilized more broadly as communication interfaces and the demands for more natural interaction measures have increased as well. Humans can express emotions in various ways...
The number of smart devices is expected to exceed 100 billion by 2050, and many will feature conversational user interfaces. Thus, methods for generating appropriate prosody for the responses of embodied conversational agents will be very important....
Driver fatigue and distracted driving are the two most common causes of major accidents. Thus, the on-board monitoring of driving behaviors is key in the development of intelligent vehicles. In this paper, we propose an approach which detects driver...
Research on facial recognition has recently been flourishing, which has led to the introduction of many robust methods. However, since the worldwide outbreak of COVID-19, people have had to regularly wear facial masks, thus making existing face recog...
In recent years, deep learning techniques have become increasingly prominent in face recognition tasks, particularly through the extraction and classification of face vectors. These vectors enable the inference of demographic attributes such as gende...
The most common aftereffect of severe burns in patients is hypertrophic scarring. Hypertrophic scars typically form following severe burns; it refers to excessive collagen production in the dermal layer during the healing process, resulting in an abn...
In the transition to fully automated driving, the interaction between drivers and vehicles is crucial as drivers’ emotions directly influence their behavior, thereby impacting traffic safety. Currently, relying solely on a backbone based on a c...
In the research of Facial Expression Recognition (FER), the inter-class of facial expression data is not evenly distributed, the features extracted by networks are insufficient, and the FER accuracy and speed are relatively low for practical applicat...
In this study, the implementation of traditional machine learning models in the intelligent management of swine is explored, focusing on the impact of LDA preprocessing on pig facial recognition using an SVM. Through experimental analysis, the kernel...
Pectin is a plant-derived heteropolysaccharide that has been implicated in drug development, tissue engineering, and visceral organ repair. Pectin demonstrates remarkable biostability in a variety of physiologic environments but is biodegradable in w...
The rapid advancement of Artificial Intelligence Generated Content (AIGC) has significantly accelerated the evolution of Deepfake technology, thereby introducing escalating social risks due to its potential misuse. In response to these adverse effect...
By leveraging artificial intelligence and big data to analyze and assess classroom conditions, we can significantly enhance teaching quality. Nevertheless, numerous existing studies primarily concentrate on evaluating classroom conditions for student...
Facial expression recognition (FER) is an important field in computer vision with many practical applications. However, one of the challenges in FER is dealing with small sample data, where the number of samples available for training machine learnin...
Emotion recognition is attracting the attention of the research community due to its multiple applications in different fields, such as medicine or autonomous driving. In this paper, we proposed an automatic emotion recognizer system that consisted o...
The development of strain sensors with high sensitivity and stretchability is essential for health monitoring, electronic skin, wearable devices, and human-computer interactions. However, sensors that combine high sensitivity and ultra-wide detection...
In this work, we propose a 3D occlusion facial recognition network based on a multi-feature combination threshold (MFCT-3DOFRNet). First, we design and extract the depth information of the 3D face point cloud, the elevation, and the azimuth angle of...
Facial expression recognition has been well studied for its great importance in the areas of human–computer interaction and social sciences. With the evolution of deep learning, there have been significant advances in this area that also surpas...
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